Matteo Richiardi - The Effects of Digital Transformation on Employment, Wages, Poverty and Inequality: A Microsimulation Study

  • Presenting author: Matteo Richiardi (Centre for Microsimulation and Policy Analysis, University of Essex)

  • Authors: Matteo Richiardi, Clare Fenwick, Leonie Westhoff

  • Session: C01A - Dynamic / Long term [2] - Wednesday 9:00-10:30 - Ceremonial Hall

Since the Industrial Revolution the public, politicians and researchers have been concerned by the possible job displacement effects and subsequently the resulting socio-economic changes that new technologies may bring. In this article we study the effects of digital transformation on employment outcomes, wage growth, poverty and income inequality in the EU between 2010 and 2019 to try to better understand how individuals and societies have been affected by digital transformation over the last decade. To measure digital transformation we construct three novel indexes: (1) digital skills endowment, (2) digital capital intensity, and (3) robot density using the Community Survey on ICT usage (ICT Survey), the EUKLEMS & INTANProd database, and robotics data from the International Federation of Robotics (IFR). We then impute these indexes to EU-SILC micro-data. In order to overcome the 4-year structure of the longitudinal panel, we perform a concatenated analysis and simulate labour market outcomes over the 10-year horizon based on the econometric results for shorter periods. Alongside this, we perform a counterfactual analysis to simulate outcomes if the digital transformation were halted for the 10 year period. Comparing baseline and counterfactual results allows us to quantify the overall impact of the transformation. Our results show that individual digital skills endowment are important for finding a job, but less so for retaining it and that this effect is reduced for individuals with higher education. Moreover, digital skills have a positive impact on gross earnings growth for those not in employment in 2010, although there is a negative effect for those with low education and starting off in employment in 2010 suggesting that this group suffers the most from digital transformation. The effects of digital capital intensity and robot density on employment and wages are limited. For inequality and poverty, the differences between the baseline scenario (digital transformation takes place) versus the counterfactual scenario (digital transformation is halted) is close to zero, meaning that according to our estimates no discernable effect on inequality and poverty can be detected.